PhysAnth Phylogeny

Sunday, September 28, 2014

I just found this document on my computer. It is a short synopsis of the history of evolutionary thought that I wrote for a class in my first year of grad school. It is not perfect or complete, but I thought it was worth posting. Please add corrections or comments below.

The theory of evolution by Darwinian natural selection is of critical importance to modern
paleontology, and the field of paleontology has had a decisive role in the
justification of the theory.Early ideas
on the natural community of life followed Plato’s Principle of Plenitude.This principle essentially stated that
everything that could exist did in fact exist, and that forms could not be
created nor could existing forms be destroyed.This principle was at the heart of the idea of the scala naturae, or the Great Chain of Being, which envisioned the
natural world as consisting of a hierarchical ordering of organisms from the simplest
to the most complex (read most perfect), from the creeping slimes to the
crowing achievement of creation, humans.Humans were merely a step below cherubim and other various categories of
angels.

Hadley Wickham has come out with yet another R package that is destined to improve my workflow and let me concentrate less on getting R to do things, and more on my research questions. The package is dplyr, a reboot of an earlier package called plyr.

Behind both packages is the notion that it should be easy to do split-apply-combine operations on your data. These operations are where you group your observations by some categorical variable, do the some operation on each subset, and then recombine results. The plyr package was already really good at this.

From my perspective, the 2 most important improvements in dplyr are

a MASSIVE increase in speed, making dplyr useful on big data sets

the ability to chain operations together in a natural order

Here is a quick example of how you can do complicated stuff with dplyr. Example data are from the PanTHERIA1 dataset of life history traits across mammals.

First, we read in the data from the web. This step takes the longest of anything we will do, because we are reading a 2.5 MB text file into memory over http. It is a huge dataset with 5416 observations of 55 variablesEdit: make sure you are using the most recent version of dplyr (0.1.1), or else you may have issues with your R session crashing.

Next we will set up some factors with human readable levels. Note that our variables aren't named very concisely, but we will leave them for now.

pantheria$X1.1_ActivityCycle <- factor(pantheria$X1.1_ActivityCycle)levels(pantheria$X1.1_ActivityCycle) <- c("nocturnal","cathermeral","diurnal")pantheria$X6.2_TrophicLevel <- factor(pantheria$X6.2_TrophicLevel)levels(pantheria$X6.2_TrophicLevel) <- c("herbivore","omnivore","carnivore")
OK. Now we are ready to show off the magic of dplyr. We will use the %.%. operator to chain together commands to manipulate our dataframe. First, we use the mutate()function to create a new column called yearlyOffspring, which is a transformation of two other columns. Then, we pass that result to the filter function, and filter out just the rodents. Next, we add a group_by() clause, and finally, we use summarise(), to calculate the average body mass for each group. Type ?manip in the command line to see the full list of dplyr manipulation functions.Activity_Trophic <-pantheria %.% mutate(yearlyOffspring = X16.1_LittersPerYear * X16.1_LittersPerYear) %.% filter(MSW05_Order == "Rodentia") %.%

Ecomorphology uses anatomical characteristics to predict the ecological context in which an organism lived. This is possible because organisms adapt anatomically to the functional requirements of their lifestyles. However, ecomorphology may be complicated by the fact that both morphological and ecological traits tend to have phylogenetic signal. In other words, closely related species tend to be more similar than more distantly related species. This can make it difficult to tease apart the effects of functional adaptation from those of phylogenetic signal.

One of the most common statistical methods in ecomorphology is DFA. The purpose of our study was to evaluate the performance of DFA in situations with varying levels of phylogenetic signal.

We used phylogenetic simulations to create datasets that were related to a phylogenetic tree, but were functionally unrelated to a set of ecological characteristics, which had varying levels of phylogenetic signal. We simulated data in which (1) both the morphological characters and ecological categories had phylogenetic signal, (2) only the morphological characters had phylogenetic signal, (3) only the ecological category had phylogenetic signal, and (4) when neither the morphology nor the category had phylogenetic signal.

Remember: in all cases there was no biomechanical connection between habitat and morphology. We then ran DFA on the resulting datasets. The results are summarized in the figure below.

This figure shows the mean success rates of DFA on the vertical axis, and % of DFAs that were significant on the horizontal axis. When we randomized habitats, DFAs were rarely significant. However, when the actual habitats (with phylogenetic signal) were used, the DFAs are very often statistically significant in cases where the morphological variables have phylogenetic signal. We used Phylogenetic Generalized Least Squares (PGLS) on these same datasets, and found that PGLS reliably rejects the hypothesis of a biomechanical link between category and morphology.

Thus, we concluded that PGLS should be used to validate characters before including them in DFA.

Wednesday, November 13, 2013

One of the most common ways people write for() loops is to create an empty results vector and then concatenate each result with the previous (and growing) results vector, like the following. (Note: wrapping an expression in the function system.time() executes the function and returns a summary of how long it took, in seconds.)

x <- c()

system.time(

for(i in 1:40000){

x<-c(x,i) #here i is combined with previous contents of x

}

)

user system elapsed

2.019 0.082 2.100

It is MUCH faster to create the results an empty vector of the correct size, and modify elements in place. This prevents R from having to move around an ever growing object in memory and is much faster. In short....it seems that what R is slow at is allocating memory for objects.

This skull is super important, because it is quite different from the other four Dmanisi skulls in that is has a massive face and jaw, and just a tiny brain at about 550cc. Thus, the authors argue that the Dmanisi sample from a single place and a relatively short time interval encompasses virtually all of the variation found in early Homo specimens from Africa. This would imply that the proposed species diversity in early Homo is not really species diversity at all, unless you want to split the Dmanisi specimen into multiple species.

The specimen is getting TONS of well-deserved press attention, but much of the coverage is predictably sensationalist....claiming that this skull overturns what we thought we knew about the human family tree. A more accurate description might be that this skull offers fresh evidence which is lending new support to a long-standing idea in paleoanthropology (i.e. that early Homo is characterized best as one species).

Saturday, September 7, 2013

A team of researchers working at Shuitangba, a site in the Miocene of China, just announced a pretty awesome juvenile cranium of the Miocene ape genus Lufengpithecus. This skull is important because of its relatively young age (about 6 million years), and because it doesn't closely resemble orangutans. Many researchers have considered Lufengpithecus to be closely related to modern orangutans, but if true, then Lufengpithecus should bear a striking resemblance to modern orangs by 6 million years ago. The authors argue that this isn't the case, and that Lufengpithecus doesn't appear similar to any modern apes. Very cool fossil!

Monday, September 2, 2013

Liza Shapiro, Brett Nachman and I have just launched a new website called Academic Phylogeny of Physical Anthropology. We are creating an interactive online genealogy of physical anthropology PhDs. The idea was hatched over lunch in the department. We were discussing the great paper by Elizabeth Kelley and Robert Sussman in which they trace the academic genealogy of field primatologists. We were lamenting the fact that there wasn't a comparable tree for other sub-specializations within physical anthropology. We decided that tracing academic history is important, and that creating an online version driven by user submissions was the best way to build out the tree.

Please check out the site. If you are a physical anthropology PhD (or know somebody who is), make sure their name appears. If it doesn't appear, be sure to add it!

Tuesday, June 18, 2013

One of the most visible fad diets lately (at least where I live) is the so-called Paleo Diet. If you haven't heard of it, you can think of the Paleo Diet as pop evolutionary psychology for foodies. Essentially, the idea is that our bodies are adapted to the diet of our "pre-agricultural, hunter gatherer ancestors", and that we should try to mimic this diet as much as possible, because it is more natural.

The basic idea is sensible enough, right? I mean, to the extent that the diet recommends doing away with the heavily processed carbs which are modern technological innovations, I think we can all get on board (leaving aside critical questions regarding poverty and food access for the moment). However, the picture gets a little less clear when we dig deeper into questions like "which ancestors are we talking about" and "what did those ancestors actually eat"? That's where the science comes in.

caveman eating burger and fries

In the June 3rd issue of PNAS, there were three important papers on the stable isotopic evidence for early hominin diet, especially hominins in East Africa. These are dense technical papers that provide invaluable direct evidence regarding the diets of our early ancestors. I won't try to summarize these papers, I just want to pick out three broad points that they drive home for me:

The diets of human ancestors are notably variable when compared with other animals.

Some foods that our ancestors have probably eaten for millions of years would be forbidden by the so-called Paleodiet.

Point 1: While the early hominin species A. anamensis had a carbon isotope signature dominated by C3 resources (Cerling et al, 2013), it is clear that by the time A. afarensis (Lucy's species) came around, they were eating lots of C4 (Wynn et al, 2013). This is interesting, because it means that a dietary transition away from ape-like diets dominated by C3 vegetation occurred really early in human evolution (around 3.4 Ma) in a species that most researchers agree is directly ancestral to us. This dietary shift seems really interesting when you consider that even chimpanzees that routinely live in open savanna environments don't eat much C4 vegetation (Schoeninger et al, 1999). Sponheimer and colleagues (2013) verify that this shift occurred in multiple species through time, and that there is a weak trend towards more C4 as time goes on.

Point 2: Human ancestors had remarkably varied diets! Wynn and colleagues (2013) show that different A. afarensis individuals had isotope values that ranged from the neighborhood of committed browsers nearly (but not quite) up to that of committed grazers. Clearly early hominins were eating lots of different things. This is consistent with a previous study suggesting that different species of the genus Paranthropus were eating remarkably different diets, even though their jaw anatomy is extremely similar.

Point 3: Stable isotope analysis can't tell us exactly which C4 plants hominins were eating. But, a likely candiate C4 food item for early humans are underground storage organs of certain C4 plants. These starchy roots and tubers would be gritty and fibrous, but would include ample carbohydrates and water. The idea that early hominins relied on these so-called underground storage organs (USOs) goes way back in paleoanthropology (Hatley and Kappelman, 1980) and had a bit of a revival in the last decade (Laden and Wrangham, 2005). It is ironic that practitioners of the paleodiet swear off starchy tubers like potatoes when they have likely been an important part of hominin diets for the last 3.4 million years!!!

Conclusion: It is really hard to know what our earliest ancestors ate. The best science is starting to paint a picture, though and it is clear that leaving behind the ape-like diet of leafy greens and fruits was an integral part of human evolution from very early days.

If we were to consider recent ancestors (say in the last 50,000 years), it would be clear that hunting and gathering human populations have made a living from every kind of diet you can imagine (think near vegetarians on one extreme and eating tons of whale blubber on the other hand)! It is far from clear what it means to "eat like a caveman" and this idea has much more to do with selling diet books than it does with the science of figuring out what our ancestors actually ate. Thankfully, we have lots of careful scientists doing the difficult task of figuring it out!

Wednesday, April 17, 2013

At last! There is a beautifully updated version of Fleagle's seminal Primate Adaptation and Evolution. Just took my first look, and it appears to include all of the many important fossil discoveries since last edition. Also, there are many new images, and the format is larger, meaning that all the images are much larger. This is great!!